Due to engineering limitations, the gradient fields used for spatial encoding in clinical magnetic resonance imaging (“MRI”) are never truly linear over the imaging field-of-view (“FOV”). As standard MRI signal models presume gradient linearity, reconstructed images exhibit geometric distortion unless gradient deviations are properly accounted for. Given a priori knowledge of the gradient field, geometric distortion due to gradient nonlinearity is typically corrected via image-domain interpolation. Although this retrospective approach, commonly termed gradient distortion correction or “GradWarp,” is straightforward, it does not explicitly account for the effects of finite sampling, undersampling, or noise, and may consequently degrade spatial resolution.
Although prospective correction has been considered in situations when gradients are intentionally distorted for encoding purposes, such as parallel imaging techniques using localized gradients (“PATLOC”), this approach has not been considered for the more common scenario where ideally linear gradients are not performing as desired.
As noted, GNL effects are conventionally corrected after image reconstruction using image-domain interpolation, which may be followed by intensity correction using the Jacobian-determinant of the distortion field. The intensity correction is necessary to compensate for GNL-induced image uniformity changes. Although this method has been shown to be effective at correcting coarse image distortions on conventional whole-body MRI systems with moderate GNL, images corrected using this method can suffer from noise amplification at regions with strong GNL distortion (e.g., the peripheral regions of the imaging volume). This problem is especially relevant for large field-of-view imaging on whole-body scanners, and for the compact systems with asymmetric gradient design. The smaller imaging volume (e.g., 26-cm diameter-spherical-volume) of these latter systems, which can be designed for brain and extremity imaging, renders the noise amplification effect to be apparent even in a brain scan FOV of 25.6 cm.
Hence, given the above, there is a need for systems and methods for accurate and efficient correction of gradient nonlinearity in magnetic resonance imaging.